plot(fit_wj, type="summary", labeltype="frex", topic.names=c("","","","","","","","","","","","","","","","","","","","","","","","",""),
custom.labels=topic_labels,topics=c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17, 18,19,20,21,22,23,24,25), text.cex=1.5, main="" )
load("~/Siegel Dropbox/Alexandra Siegel/0202/wj_stm.RData")
plot(fit, type="summary", labeltype="frex", topic.names=c("","","","","","","","","","","","","","","","","","","","","","","","",""),
custom.labels=topic_labels,topics=c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17, 18,19,20,21,22,23,24,25), text.cex=1.5, main="" )
topic_labels<-c("Cleaning",
"Education",
"Pets",
"Volunteering",
"Lost and Found",
"Parenting",
"English",
"Prayer",
"Concerts",
"Food and Restaurants",
"Spa Services",
"Transportation",
"Honoring / Remembering",
"Infrastructure",
"Apartments/Homes",
"For Sale",
"Prayer",
"Business",
"Employment",
"Yard Sale",
"Yoga/Meditation",
"Vacations",
"Temple Mount",
"Entertainment",
"Covid"
)
plot(fit, type="summary", labeltype="frex", topic.names=c("","","","","","","","","","","","","","","","","","","","","","","","",""),
custom.labels=topic_labels,topics=c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17, 18,19,20,21,22,23,24,25), text.cex=1.5, main="" )
dev.off()
plot(fit, type="summary", labeltype="frex", topic.names=c("","","","","","","","","","","","","","","","","","","","","","","","",""),
custom.labels=topic_labels,topics=c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17, 18,19,20,21,22,23,24,25), text.cex=1.5, main="" )
plot(fit, type="summary", labeltype="frex", custom.labels=topic_labels,topics=c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17, 18,19,20,21,22,23,24,25) )
plot(fit, type="summary", labeltype="frex", custom.labels=topic_labels,topics=c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17, 18,19,20,21,22,23,24,25) )
topic_labels<-c("Cleaning",
"Education",
"Pets",
"Volunteering",
"Lost and Found",
"Parenting",
"English",
"Prayer",
"Concerts",
"Food and Restaurants",
"Spa Services",
"Transportation",
"Honoring / Remembering",
"Infrastructure",
"Apartments/Homes",
"For Sale",
"Prayer",
"Business",
"Employment",
"Yard Sale",
"Yoga/Meditation",
"Vacations",
"Entertainment",
"Temple Mount",
"COVID"
)
topic_labels<-c("Cleaning",
"Education",
"Pets",
"Volunteering",
"Lost and Found",
"Parenting",
"English",
"Prayer",
"Concerts",
"Food and Restaurants",
"Spa Services",
"Transportation",
"Honoring / Remembering",
"Infrastructure",
"Apartments/Homes",
"For Sale",
"Prayer",
"Business",
"Employment",
"Yard Sale",
"Yoga/Meditation",
"Vacations",
"Entertainment",
"Temple Mount",
"COVID"
)
pdf("figure_2b.pdf", height=7, width=11)
plot(fit_wj, type="summary", labeltype="frex", topic.names=c("","","","","","","","","","","","","","","","","","","","","","","","",""),
custom.labels=topic_labels,topics=c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17, 18,19,20,21,22,23,24,25), text.cex=1.5, main="" )
load("west_jerusalem_stm.RData")
topic_labels<-c("Cleaning",
"Education",
"Pets",
"Volunteering",
"Lost and Found",
"Parenting",
"English",
"Prayer",
"Concerts",
"Food and Restaurants",
"Spa Services",
"Transportation",
"Honoring / Remembering",
"Infrastructure",
"Apartments/Homes",
"For Sale",
"Prayer",
"Business",
"Employment",
"Yard Sale",
"Yoga/Meditation",
"Vacations",
"Entertainment",
"Temple Mount",
"COVID"
)
pdf("figure_2b.pdf", height=7, width=11)
plot(fit_wj, type="summary", labeltype="frex", topic.names=c("","","","","","","","","","","","","","","","","","","","","","","","",""),
custom.labels=topic_labels,topics=c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17, 18,19,20,21,22,23,24,25), text.cex=1.5, main="" )
dev.off()
pdf("figure_2b.pdf", height=8, width=11)
plot(fit_wj, type="summary", labeltype="frex", topic.names=c("","","","","","","","","","","","","","","","","","","","","","","","",""),
custom.labels=topic_labels,topics=c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17, 18,19,20,21,22,23,24,25), text.cex=1.5, main="" )
dev.off()
topic_labels<-c("Cleaning",
"Education",
"Pets",
"Volunteering",
"Lost and Found",
"Parenting",
"English",
"Prayer",
"Concerts",
"Food and Restaurants",
"Spa Services",
"Transportation",
"Honoring / Remembering",
"Infrastructure",
"Apartments/Homes",
"For Sale",
"Torah Verses",
"Business",
"Employment",
"Yard Sale",
"Yoga/Meditation",
"Vacations",
"Entertainment",
"Temple Mount",
"COVID"
)
pdf("figure_2b.pdf", height=8, width=11)
plot(fit_wj, type="summary", labeltype="frex", topic.names=c("","","","","","","","","","","","","","","","","","","","","","","","",""),
custom.labels=topic_labels,topics=c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17, 18,19,20,21,22,23,24,25), text.cex=1.5, main="" )
dev.off()
topic_labels<-c("Cleaning",
"Education",
"Pets",
"Volunteering",
"Lost and Found",
"Parenting",
"English",
"Torah Verses",
"Concerts",
"Food and Restaurants",
"Spa Services",
"Transportation",
"Honoring / Remembering",
"Infrastructure",
"Apartments/Homes",
"For Sale",
"Prayer",
"Business",
"Employment",
"Yard Sale",
"Yoga/Meditation",
"Vacations",
"Entertainment",
"Temple Mount",
"COVID"
)
pdf("figure_2b.pdf", height=8, width=11)
plot(fit_wj, type="summary", labeltype="frex", topic.names=c("","","","","","","","","","","","","","","","","","","","","","","","",""),
custom.labels=topic_labels,topics=c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17, 18,19,20,21,22,23,24,25), text.cex=1.5, main="" )
dev.off()
# Project Info----------------------------------------------------------------------
#  Project: Outgroup Avoidance
#  Purpose: Plot results of structural topic models
#  Outputs: Figure 2
# load all relevant packages--------------------
library("stm")
# load data-------
load("east_jerusalem_stm.RData")
load("west_jerusalem_stm.RData")
# Main Text------
## Figure 2a (East Jerusalem) -----
topic_labels<-c("Movement Restrictions",
"Death/Mourning",
"Donations",
"Religious Advice",
"Prayer",
"For Sale",
"Funerals",
"Demolitions/Destruction",
"Quran Verses",
"Weddings",
"Utilities",
"Prisoners",
"Martyrs",
"For Rent",
"Holidays (Eid)",
"School/Education",
#"Topic 17",
"Violence/Clashes",
"Israeli Crimes",
"Weather",
#"Topic 21",
"COVID",
"Palestine News",
"Soccer",
"Foreign News"
)
pdf("figure_2a.pdf", height=11, width=11)
plot(fit_ej, type="summary", labeltype="frex", topic.names=c("","","","","","","","","","","","","","","","","","","","","","",""),
custom.labels=topic_labels,topics=c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,18,19,20,22,23,24,25), text.cex=1.7,main="" )
dev.off()
## Figure 2b (West Jerusalem)----
topic_labels<-c("Cleaning",
"Education",
"Pets",
"Volunteering",
"Lost and Found",
"Parenting",
"English",
"Torah Verses",
"Concerts",
"Food and Restaurants",
"Spa Services",
"Transportation",
"Honoring / Remembering",
"Infrastructure",
"Apartments/Homes",
"For Sale",
"Prayer",
"Business",
"Employment",
"Yard Sale",
"Yoga/Meditation",
"Vacations",
"Entertainment",
"Temple Mount",
"COVID"
)
pdf("figure_2b.pdf", height=8, width=11)
plot(fit_wj, type="summary", labeltype="frex", topic.names=c("","","","","","","","","","","","","","","","","","","","","","","","",""),
custom.labels=topic_labels,topics=c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17, 18,19,20,21,22,23,24,25), text.cex=1.5, main="" )
dev.off()
# Project Info----------------------------------------------------------------------
#  Project: Outgroup Avoidance
#  Purpose: Plot results of structural topic models
#  Outputs: Figure 2
# load all relevant packages--------------------
library("stm")
# load data-------
load("east_jerusalem_stm.RData")
load("west_jerusalem_stm.RData")
# Main Text------
## Figure 2a (East Jerusalem) -----
topic_labels<-c("Movement Restrictions",
"Death/Mourning",
"Donations",
"Religious Advice",
"Prayer",
"For Sale",
"Funerals",
"Demolitions/Destruction",
"Quran Verses",
"Weddings",
"Utilities",
"Prisoners",
"Martyrs",
"For Rent",
"Holidays (Eid)",
"School/Education",
#"Topic 17",
"Violence/Clashes",
"Israeli Crimes",
"Weather",
#"Topic 21",
"COVID",
"Palestine News",
"Soccer",
"Foreign News"
)
pdf("figure_2a.pdf", height=11, width=11)
plot(fit_ej, type="summary", labeltype="frex", topic.names=c("","","","","","","","","","","","","","","","","","","","","","",""),
custom.labels=topic_labels,topics=c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,18,19,20,22,23,24,25), text.cex=1.7,main="" )
dev.off()
## Figure 2b (West Jerusalem)----
topic_labels<-c("Cleaning",
"Education",
"Pets",
"Volunteering",
"Lost and Found",
"Parenting",
"English",
"Torah Verses",
"Concerts",
"Food and Restaurants",
"Spa Services",
"Transportation",
"Honoring / Remembering",
"Infrastructure",
"Apartments/Homes",
"For Sale",
"Prayer",
"Business",
"Employment",
"Yard Sale",
"Yoga/Meditation",
"Vacations",
"Entertainment",
"Temple Mount",
"COVID"
)
pdf("figure_2b.pdf", height=8, width=11)
plot(fit_wj, type="summary", labeltype="frex", topic.names=c("","","","","","","","","","","","","","","","","","","","","","","","",""),
custom.labels=topic_labels,topics=c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17, 18,19,20,21,22,23,24,25), text.cex=1.5, main="" )
dev.off()
fit_ej
fit_wj
# Project Info----------------------------------------------------------------------
#  Project: Outgroup Avoidance
#  Purpose: Plot results of structural topic models
#  Outputs: Figure 2
# load all relevant packages--------------------
library("stm")
# load data-------
load("east_jerusalem_stm.RData")
load("west_jerusalem_stm.RData")
# Main Text------
## Figure 2a (East Jerusalem) -----
topic_labels_ej<-c("Movement Restrictions",
"Death/Mourning",
"Donations",
"Religious Advice",
"Prayer",
"For Sale",
"Funerals",
"Demolitions/Destruction",
"Quran Verses",
"Weddings",
"Utilities",
"Prisoners",
"Martyrs",
"For Rent",
"Holidays (Eid)",
"School/Education",
#"Topic 17",
"Violence/Clashes",
"Israeli Crimes",
"Weather",
#"Topic 21",
"COVID",
"Palestine News",
"Soccer",
"Foreign News"
)
pdf("figure_2a.pdf", height=11, width=11)
plot(fit_ej, type="summary", labeltype="frex", topic.names=c("","","","","","","","","","","","","","","","","","","","","","",""),
custom.labels=topic_labels_ej,topics=c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,18,19,20,22,23,24,25), text.cex=1.7,main="" )
dev.off()
## Figure 2b (West Jerusalem)----
topic_labels_wj<-c("Cleaning",
"Education",
"Pets",
"Volunteering",
"Lost and Found",
"Parenting",
"English",
"Torah Verses",
"Concerts",
"Food and Restaurants",
"Spa Services",
"Transportation",
"Honoring / Remembering",
"Infrastructure",
"Apartments/Homes",
"For Sale",
"Prayer",
"Business",
"Employment",
"Yard Sale",
"Yoga/Meditation",
"Vacations",
"Entertainment",
"Temple Mount",
"COVID"
)
pdf("figure_2b.pdf", height=8, width=11)
plot(fit_wj, type="summary", labeltype="frex", topic.names=c("","","","","","","","","","","","","","","","","","","","","","","","",""),
custom.labels=topic_labels_wj,topics=c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17, 18,19,20,21,22,23,24,25), text.cex=1.5, main="" )
dev.off()
load("east_jerusalem_stm.RData")
load("west_jerusalem_stm.RData")
View(fit_ej)
topic_labels_ej<-c("Movement Restrictions",
"Death/Mourning",
"Donations",
"Religious Advice",
"Prayer",
"For Sale",
"Funerals",
"Demolitions/Destruction",
"Quran Verses",
"Weddings",
"Utilities",
"Prisoners",
"Martyrs",
"For Rent",
"Holidays (Eid)",
"School/Education",
#"Topic 17",
"Violence/Clashes",
"Israeli Crimes",
"Weather",
#"Topic 21",
"COVID",
"Palestine News",
"Soccer",
"Foreign News"
)
pdf("figure_2a.pdf", height=11, width=11)
plot(fit_ej, type="summary", labeltype="frex", topic.names=c("","","","","","","","","","","","","","","","","","","","","","",""),
custom.labels=topic_labels_ej,topics=c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,18,19,20,22,23,24,25), text.cex=1.7,main="" )
# Project Info----------------------------------------------------------------------
#  Project: Outgroup Avoidance
#  Purpose: Plot results of structural topic models
#  Outputs: Figure 2
# load all relevant packages--------------------
library("stm")
# load data-------
load("east_jerusalem_stm.RData")
load("west_jerusalem_stm.RData")
# Main Text------
## Figure 2a (East Jerusalem) -----
topic_labels_ej<-c("Movement Restrictions",
"Death/Mourning",
"Donations",
"Religious Advice",
"Prayer",
"For Sale",
"Funerals",
"Demolitions/Destruction",
"Quran Verses",
"Weddings",
"Utilities",
"Prisoners",
"Martyrs",
"For Rent",
"Holidays (Eid)",
"School/Education",
#"Topic 17",
"Violence/Clashes",
"Israeli Crimes",
"Weather",
#"Topic 21",
"COVID",
"Palestine News",
"Soccer",
"Foreign News"
)
pdf("figure_2a.pdf", height=11, width=11)
plot(fit_ej, type="summary", labeltype="frex", topic.names=c("","","","","","","","","","","","","","","","","","","","","","",""),
custom.labels=topic_labels_ej,topics=c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,18,19,20,22,23,24,25), text.cex=1.7,main="" )
dev.off()
## Figure 2b (West Jerusalem)----
topic_labels_wj<-c("Cleaning",
"Education",
"Pets",
"Volunteering",
"Lost and Found",
"Parenting",
"English",
"Torah Verses",
"Concerts",
"Food and Restaurants",
"Spa Services",
"Transportation",
"Honoring / Remembering",
"Infrastructure",
"Apartments/Homes",
"For Sale",
"Prayer",
"Business",
"Employment",
"Yard Sale",
"Yoga/Meditation",
"Vacations",
"Entertainment",
"Temple Mount",
"COVID"
)
pdf("figure_2b.pdf", height=8, width=11)
plot(fit_wj, type="summary", labeltype="frex", topic.names=c("","","","","","","","","","","","","","","","","","","","","","","","",""),
custom.labels=topic_labels_wj,topics=c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17, 18,19,20,21,22,23,24,25), text.cex=1.5, main="" )
dev.off()
fit_ej
fit_wj
